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The relationship between variation in time perspectives and collaborative performance is scarcely explored, and even less is known about the respective mechanisms that lead to varying task performance. Thus, we aim to further the literature on time perspectives and collaborative performance, shedding light on the underlying behavioral patterns.

We report a quasi-experiment analyzing the impact of past, present and future orientation variation in dyads (N = 76) on their quantitative and qualitative performance when confronted with a simple incentivized creative task with constraints. Subsequently, we offer a qualitative analysis of comments given by the participants after the task on the collaboration.

Results indicate that a dyad's elevation of past orientation and diversity in future orientation negatively affect collaborative performance. At the same time, there is a positive effect of elevation of future orientation. The positive effect is driven by clear communication and agreement during the task, while the negative effect arises from work sharing and complementation.

This study provides insights for organizations on composing individuals regarding their temporal focus for collaborative tasks that should be executed rapidly and require creative solutions.

Our study distinguishes by considering the composition of past, present and future time perspectives in dyads and focuses on a creative task setting. Moreover, we explore the mechanisms in the dyads with a substantial elevation of/diversity in future orientation, leading to their stronger/weaker performance.

Engaging with heritage to support mental health and wellbeing has become a focus of research and policy, more recently moving towards social prescription of heritage interventions. While there are benefits to active participation, there are potential risks to those taking part and to the non-renewable historic remains and landscape that form the core of these projects. The purpose of the current research paper was to develop best practice guidelines for organisations offering heritage projects as interventions for people who live with mental health issues to protect both participants and heritage.

There were two research phases; a Sandpit with World Café discussions to produce a set of research priorities, and a Delphi Consultation, using three questionnaires distributed over six months, to develop best practice guidelines. The panel in both phases comprised experts through lived experience, policy, practice and research.

The Authentic and Meaningful Participation in Heritage or Related Activities (AMPHORA) guidelines cover three stages: project development, project delivery and project follow-up, with a set of action points for each stage. Of particular importance was authentic participation and expertise to ensure appropriate management of heritage/ historic environment assets and support for participants.

The AMPHORA guidelines can assist all organisations in the delivery of safe projects that support the mental health of those involved, as well as enhancing and protecting the historic environment.

To the best of the authors’ knowledge, these are the first research-led guidelines that help heritage organisations support those living with mental health issues.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Artificial intelligence (AI) has become increasingly important and influential in reading and writing. The influx of social media digital spaces, like TikTok, has also shifted the ways multimodal composition takes place alongside AI. This study aims to argue that within spaces like TikTok, human composers must attend to the ways they write for, with and against the AI-powered algorithm.

Data collection was drawn from a larger study on #BookTok (the TikTok subcommunity for readers) that included semi-structured interviews including watching and reflecting on a TikTok they created. The authors grounded this study in critical posthumanist literacies to analyze and open code five #BookTok content creators’ interview transcripts. Using axial coding, authors collaboratively determined three overarching and entangled themes: writing for, with and against.

Findings highlight the nuanced ways #BookTokers consider the AI algorithm in their compositional choices, namely, in the ways how they want to disseminate their videos to a larger audience or more niche-focused community. Throughout the interviews, participants revealed how the AI algorithm was situated differently as both audience member, co-author and censor.

This study is grounded in critical posthumanist literacies and explores composition as a joint accomplishment between humans and machines. The authors argued that it is necessary to expand our human-centered notions of what it means to write for an audience, to co-author and to resist censorship or gatekeeping.

This study aims to minimize the transportation-related cost in distribution while utilizing a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach. An increased cost in distribution is a major problem for many companies due to the absence of efficient planning methods to overcome operational challenges in distinct distribution networks. The problem addressed in this study is to minimize the transportation-related cost in distribution while using a heterogeneous fixed fleet to deliver distinct demand at different geographical locations with a proper workload balancing approach which has not gained the adequate attention in the literature.

This study formulated the transportation problem as a vehicle routing problem with a heterogeneous fixed fleet and workload balancing, which is a combinatorial optimization problem of the NP-hard category. The model was solved using both the simulated annealing and a genetic algorithm (GA) adopting distinct local search operators. A greedy approach has been used in generating an initial solution for both algorithms. The paired t-test has been used in selecting the best algorithm. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet compositions of the heterogeneous fleet. Results were analyzed using analysis of variance (ANOVA) and Hsu’s MCB methods to identify the best scenario.

The solutions generated by both algorithms were subjected to the t-test, and the results revealed that the GA outperformed in solution quality in planning a heterogeneous fleet for distribution with load balancing. Through a number of scenarios, the baseline conditions of the problem were further tested investigating the alternative fleet utilization with different compositions of the heterogeneous fleet. Results were analyzed using ANOVA and Hsu’s MCB method and found that removing the lowest capacities trucks enhances the average vehicle utilization with reduced travel distance.

The developed model has considered both planning of heterogeneous fleet and the requirement of work load balancing which are very common industry needs, however, have not been addressed adequately either individually or collectively in the literature. The adopted solution methodologies to solve the NP-hard distribution problem consist of metaheuristics, statistical analysis and scenario analysis are another significant contribution. The planning of distribution operations not only addresses operational-level decision, through a scenario analysis, but also strategic-level decision has also been considered.

The planning of distribution operations not only addresses operational-level decisions, but also strategic-level decisions conducting a scenario analysis.

This study aimed to propose a performance-oriented approach of automatically generative design and optimization of hospital building layouts in consideration of public health emergency, which intended to conduct reasonable layout design of hospital building to meet different performance requirements for both high efficiency during normal periods and low risk in the pandemic.

The research design follows a sequential mixed methodology. First, key points and parameters of hospital building layout design (HBLD) are analyzed. Then, to meet the requirements of high efficiency and low risk, adjacent preference score and infection risk coefficient are constructed as constraints. On this basis, automatic generative design is conducted to generate building layout schemes. Finally, multi-objective deviation analysis is carried out to obtain the optimal scheme of hospital building layouts.

Automatic generative design of building layouts that integrates adjacent preferences and infection risks enables hospitals to achieve rapid transitions between normal (high efficiency) and pandemic (low risk) periods, which can effectively respond to public health emergencies. The proposed approach has been verified in an actual project, which can help systematically explore the solution for better decision-making.

The form of building layouts is limited to rectangles, and future work can explore conducting irregular layouts into optimization for the framework of generative design.

The contribution of this paper is the developed approach that can quickly and effectively generate more hospital layout alternatives satisfying high operational efficiency and low infection risk by formulating space design rules, which is of great significance in response to public health emergency.

The purpose of this paper is to understand how those involved in executive pay determination in large publicly quoted UK businesses see the role of diversity within remuneration committees (Remcos) as enabling the input of different perspectives, which can enhance their decision-making and potentially improve pay outcomes.

Qualitative, semi-structured interviews were undertaken with 18 high-profile major-enterprise decision-makers and their advisers, i.e. non-executive directors (NEDs) serving Remcos, institutional investors, executive pay consultants and internal human resources (HR) reward specialists, together with data from three focus groups with 10 further reward management practitioners.

Remco members recognise the benefits of social category/demographic diversity but say the likelihood of increasing this is low, given talent pipeline issues. The widening of value diversity is considered problematic for Remcos’ functioning. Informational diversity is used as a proxy for social category/demographic diversity to improve Remcos’ decision-making on executive pay. While the inclusion of members from wider social networks is recognised as potentially bringing a different informational perspective, the social character of Remcos, reflecting their elite nature and experience of wealth, appears ingrained.

Our original contribution is to extend the application of upper echelons theory in the context of Remco decision-making to explain why members do not welcome widening informational diversity by appointing people from different social networks who lack value similarity. Instead, by drawing views from employees, HR acts as a proxy for social network informational diversity. The elite, upper-echelons nature of Remco appointments remains unchanged and team functioning is not disrupted.

Research on electric sports (eSports) has experienced significant growth in recent years as a consequence of increasing connectivity, institutionalization, and technological advances. However, the interdisciplinary nature of the eSports as a field and the burgeoning growth in eSports articles have rendered it necessary to conduct a systematic review of extant literature to take stock of the knowledge accumulated. To this end, we aim to undertake a comprehensive review of extant literature that takes stock of published research to derive opportunities for future research in the realm of eSports. In so doing, we contribute to the advancement of the field by mapping out the knowledge trajectory of eSports research and elucidating areas that have remained underexplored thus far.

To conduct systematic review of the eSports literature, we employed a framework that included six essential steps: protocol, search, appraisal, synthesis, analysis, and report. This comprehensive approach enables us to meticulously investigate the existing body of literature on eSports and identify key trends and topics addressed within the field. By conducting the multidisciplinary systematic literature review, we thoroughly assess the current state of eSports literature and subsequently outline potential research avenues that can contribute to eSports fields.

This study draws on a six-phase framework – member preparation, team formation, character selection, team coordination, team performance, and team reflection – to illustrate the roles played by different levels of analysis unit (i.e. characters, players, and teams) and three distinct yet interconnected stages (i.e. inputs, process, and outputs) within eSports games as well as the research opportunities it brings.

We conducted a rigorous systematic review of the eSports literature by using quantitative citation analysis and qualitative content analysis. Furthermore, we adopted team dynamic view of eSports to identify potential research avenues for future research that contribute to advancing our understanding of the eSports tournaments.

This study aims to provide insights into gender diversity in Pakistani boardrooms, particularly for the dominant family business type, which is strongly guided by (non-financial) family-related objectives when making business decisions, such as the appointment of board members. Pakistani companies operate within the framework of weak legal institutions and a traditionally highly patriarchal environment. This study examines how corporate decisions regarding the appointment of female board members play out in this socio-political and cultural environment.

Board composition and board characteristics were examined using hand-collected data from 213 listed family firms and non-family firms on the Pakistan Stock Exchange from 2003 to 2017. Univariate analyses, probit regressions and robustness tests were performed.

Pakistani family firms have a significantly higher proportion of women on their boards than do non-family firms. They are also significantly more likely to appoint women to top positions, such as CEO or chairs.

Evidently, women are allowed to enter boards through family affiliations. Gender quotas appear an ineffective instrument for breaking through the “glass ceiling” in this socio-cultural environment. Thus, gender parity must entail the comprehensive promotion of women and the enforcement of legal reforms for structural and cultural change.

The analysis focuses on a Muslim-majority emerging Asian market that has been scarcely researched, thus offering new perspectives and insights into board composition and corporate governance that go beyond the well-studied Western countries.

The effects of board composition on performance have long been discussed in management research using fractionalization measures. In this study, we propose an alternative measurement approach based on board polarization.

Using an exploratory analysis and applying the polarization measure to German Deutscher Aktienindex (DAX)-, Midcap-DAX (MDAX)- and Small Cap-Index (SDAX)-listed companies, this paper applies the polarization index to examine the relationship between board diversity and performance.

The results show that the polarization concept is well suited to measure principal-agent problems between the members of the management and supervisory boards. We reveal that board polarization is negatively associated with firm performance, as measured by return on investment (ROI).

This exploratory study shows that the measurement of board polarization can be linked to performance differences between companies, which offers promising starting points for further research.